On the Impact of Anonymization on the Performance of Large Language Models
As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has become a critical practice. However, the impact of this anonymization on model utility is not well understood. This paper presents a systematic empirical study of the trade-...
Tobias Deußer, Max Hahnbück, L. Sparrenberg et al.
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